A journey of business analytics in improving supply chain performance: A systematic review of literature.
By: Chatterjee, Ayan and Chatterjee, Debmallya
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BookPublisher: Management and Labour Studies Description: 49(2), May, 2024: p.337-361.Subject(s): Business Analytics, Supply Chain Performance, Endogenous Variables, Systematic Literature Review (SLR), Market Competition, Moderating Variable, Mediating Variable, Directional Relationships, Supply Chain Dynamics, Data-Driven Decision-Making, Performance Measurement| Item type | Current location | Call number | Vol info | Status | Date due | Barcode |
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Indian Institute of Public Administration | 49(2), May, 2024: p.337-361 | Available | AR132116 |
The influence of business analytics on supply chain performance has become notable over the last decade. The purpose of this study is to identify and analyze the effect of endogenous variables of business analytics, if any, on supply chain performance. We have conducted a systematic literature review (SLR) in four sequential stages, that is, collecting existing literature from relevant databases, finding endogenous variable(s) in this context, classifying papers based on how the endogenous variable(s) under consideration affect the impact of business analytics on supply chain performance and, finally, segmenting the literature depending on different types of supply chain performance. The study considers research papers published during the period 2008–2023. Based on the analysis of the literature, it is found that ‘market competition’ is an important endogenous variable in this context. This variable can impact the relationship between business analytics and supply chain performance in different ways. It can serve as a moderating variable, mediating variable or main variable. In this study, we have shown how directional relationships among business analytics, market competition and supply chain performance have changed over time. The future scope of the proposed study could be to identify other endogenous variables at the time of verifying the influence of business analytics on supply chain performance. – Reproduced
https://journals.sagepub.com/doi/full/10.1177/0258042X231208586


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